An Activity System-based Perspective of Generative AI : Challenges and Research Directions

Research output: Journal Publications and ReviewsEditorial Preface

9 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)247-267
Journal / PublicationAIS Transactions on Human-Computer Interaction
Volume15
Issue number3
Publication statusPublished - Sept 2023

Abstract

With its remarkable ability to generate content, generative artificial intelligence (GAI) has been recognized as a milestone in the development of artificial general intelligence. To understand the challenges, potential impact, and implications associated with GAI, we adopt a socio-technical perspective to analyze them. First, we identify the key characteristics of GAI, which include content generation, generalization ability, and reinforcement learning based on human feedback. Next, we address technological, ethical, societal, economic, regulatory, and governance challenges. Finally, we deploy activity theory to explore research directions in GAI. Research questions that warrant further investigation include how GAI may impact the future of work, how GAI can collaborate effectively with humans, and how we can improve the transparency of GAI models as well as mitigate biases and misinformation in GAI to achieve ethical and responsible GAI. © 2023 by the Association for Information Systems.

Research Area(s)

  • Activity System Analysis, Activity Theory, AI Challenges, Generative Artificial Intelligence, Research Directions, Socio-technical Perspective